Prevalence of Prediabetes and Diabetes Mellitus Type II in Bipolar Disorder

Presentation and Management of Acute Mania in Fanconi-Bickel Syndrome, A Metabolic Genetic Disorder

Fanconi-Bickel syndrome (FBS) is a rare metabolic disorder caused by decreased glucose transporter 2 (GLUT2) function due to several known mutations in the SLC2A2 gene. As of 2020, 144 cases of FBS have been described in the literature. Metabolic and somatic sequelae include dysglycemia and accumulation of glycogen in the kidney and liver. However, there are no descriptions in the literature of possible neuropsychiatric manifestations of FBS. This case report is to our knowledge the first in this regard, describing a patient with FBS who was admitted to our psychiatric inpatient unit while experiencing acute mania. We conceptualize the case as a novel psychiatric presentation of acute mania in FBS, which may inform our understanding of bipolar disorder pathophysiology because of the hypothesized functional changes in neural pathways involving the paraventricular thalamus induced by decreased GLUT2 activity in FBS.

Diabetes mellitus in patients with chronic bipolar disorder: prevalence, clinical correlates and relationship with homocysteine

Comorbid diabetes mellitus in patients with bipolar disorder may contribute to increased morbidity and mortality. To determine the prevalence of diabetes mellitus in bipolar disorder patients and its clinico-demographic and homocysteine correlates, we conducted a cross-sectional survey of 195 bipolar disorder inpatients. They received questionnaires, clinical measurements and laboratory tests to assess demographic characteristics, anthropometric variables, clinical variables and plasma homocysteine levels. The prevalence of diabetes mellitus (including type 1, type 2 and special types) in Chinese bipolar disorder patients was 14.9%. Analysis of variance or chi-square test showed that compared with non-diabetic bipolar disorder patients, diabetic bipolar disorder patients were older, more often married, had a longer duration of disease, took less olanzapine and had a higher frequency of hypertension. However, there were no significant differences in body mass index (BMI) and homocysteine levels between diabetic and non-diabetic bipolar disorder patients. Logistic regression analysis showed that marital status and duration of disease were independently associated with diabetes mellitus in patients with bipolar disorder after controlling for age, use of olanzapine, presence of hypertension, BMI and homocysteine levels. These findings shed light on the clinico-demographic correlates of the increased prevalence of diabetes mellitus in bipolar disorder patients, rather than the correlation with some metabolic risk factors.

Type 2 Diabetes and Its Association With Psychiatric Disorders in Young Adults in South Korea

Importance

Because type 2 diabetes (T2D) has become increasingly prevalent among young adults, the study of the association of T2D with psychiatric disorders in young adults is important for early detection and timely intervention.

Objective

To determine whether a diagnosis of a psychiatric disorder is associated with increased risk of developing T2D in young adults.

Design, Setting, and Participants

This large-scale prospective cohort study used data collected by the South Korean National Health Insurance Service between 2009 and 2012, representing 97% of the South Korean population. Young adults aged 20 to 39 years with and without diagnoses of psychiatric disorders were included in the study. Young adults with missing data and those with a history of T2D were excluded from the study. The cohort was followed up to monitor development of T2D until December 2018. Data were analyzed from March 2021 to February 2022.

Exposure

Diagnosis of 1 of 5 psychiatric disorders, including schizophrenia, bipolar disorder, depressive disorder, anxiety disorder, and sleep disorder.

Main Outcomes and Measures

The primary outcome was newly diagnosed T2D during a follow-up period of 7.59 years. The incidence rate of T2D was calculated as the number of new cases per 1000 person-years during the follow-up period. The Cox proportional hazards regression model was used to estimate the hazard ratios (HRs) and 95% CIs for T2D incidence. Exploratory analyses were performed for subgroups stratified by age and sex.

Results

In total, 6 457 991 young adults (mean [SD] age, 30.74 [4.98] years; 3 821 858 men [59.18%]) were followed up, including 658 430 individuals with psychiatric disorders. The cumulative incidence of T2D differed significantly between individuals with and without psychiatric disorders (log-rank test, P < .001). Incidence rates of T2D for individuals with and without psychiatric disorders were 2.89 and 2.56 per 1000 person-years, respectively. Individuals with a diagnosis of any psychiatric disorder showed a higher risk of developing T2D than those without a diagnosis (adjusted HR, 1.20; 95% CI, 1.17-1.22). The adjusted HRs for T2D were 2.04 (95% CI, 1.83-2.28) for individuals with schizophrenia, 1.91 (95% CI, 1.73-2.12) for individuals with bipolar disorder, 1.24 (95% CI, 1.20-1.28) for individuals with depressive disorder, 1.13 (95% CI, 1.11-1.16) for individuals with anxiety disorder, and 1.31 (95% CI, 1.27-1.35) for individuals with sleep disorder.

Conclusions and Relevance

In this large-scale prospective cohort study of young adults, 5 psychiatric disorders were significantly associated with an increased risk of developing T2D. Young adults with schizophrenia and bipolar disorder in particular were at a higher risk of T2D. These results have important implications for early detection of and timely intervention in T2D for young adults with psychiatric disorders.

Analysis of the correlations between insomnia and mental health during the COVID-19 pandemic in Germany

Objective

This study evaluates correlations between insomnia and mental health during the COVID-19 pandemic in Germany.

Methods

The internet-based International COVID-19 Sleep Study (ICOSS) questionnaire including sociodemographic questions as well as sleep- and emotion-related scales was distributed in Germany during the COVID-19 pandemic from May 1 to September 30, 2020. Insomnia and mental state were assessed using the Insomnia Severity Index (ISI), Patient Health Questionnaire (PHQ), Generalized Anxiety Disorder (GAD-2), and visual analogue scale. Qualitative analyses of demographic characteristics were performed and correlation analyses of the variables calculated.

Results

A total of 1103 individuals participated and 858 valid questionnaires (70.61% females) were obtained. Mean age and body mass index were 41.97 ± 12.9 years and 26 ± 5.9 kg/m², respectively. Most participants were married (n = 486, 56.6%), living in the city (n = 646, 75.3%), and white (n = 442, 51.5%). The prevalence of insomnia, anxiety, and depression was 19.5% (ISI > 7), 6.6% (GAD-2 > 3), and 4.8% (PHQ-2 > 3), respectively. Compared to the insomnia group, the mean and median ISI, PHQ‑4, PHQ‑2, and GAD‑2 scores of the non-insomnia group were lower, while their mean and median quality of life and quality of health scores were significantly higher (P < 0.05). Pearson correlation analysis showed a positive correlation between the ISI and PHQ‑2 (r = 0.521, P < 0.001), GAD‑2 (r = 0.483, P < 0.001), and PHQ‑4 scores (r = 0.562, P < 0.001); however, the ISI score negatively correlated with the quality of life (r = −0.490, P < 0.001) and quality of health scores (r = −0.437, P < 0.001).

Conclusion

Insomnia, anxiety, and depression were very prevalent during the pandemic. Anxiety and depression were more severe in the insomnia than in the non-insomnia group, and insomnia and mental health are closely related.

Prevalence of type 2 diabetes mellitus, impaired fasting glucose, general obesity, and abdominal obesity in patients with bipolar disorder: A systematic review and meta-analysis

OBJECTIVES

The study herein aimed to assess the prevalence of type 2 diabetes mellitus (T2DM), impaired fasting glucose (IFG), as well as general and abdominal obesity in patients with bipolar disorder (BD). We also compared the prevalence of T2DM and general obesity in patients with BD with age- and gender-matched healthy controls.

METHODS

A systematic search of Embase, Medline, PubMed, and APA PsycArticles was conducted from inception to June 2021 without language restrictions. Methodological quality was assessed using the Newcastle-Ottawa Scale (NOS) modified for case-control studies.

RESULTS

A total of forty-nine studies were included in this analysis. The pooled prevalence of T2DM was 9.6% (95% CI, 7.3-12.2%). Patients with BD had a nearly 1.6 times greater risk of developing T2DM compared to their age- and gender-matched controls (RR=1.57, 95% CI 1.36-1.81, p<0.001). In the present analysis, IFG is defined as a fasting plasma glucose (FPG) ≥ 100 mg/dL (FPG≥100) with a prevalence of 22.4% (95% CI, 16.7-28.7%), or as an FPG equal to or greater than 110 mg/d (FPG≥110) with a prevalence of 14.8% (95% CI, 10.8-19.3%). The prevalence of general obesity (BMI≥30 kg/m²) was 29.0% (95% CI, 22.8-35.6%); the risk of obesity was almost twice the rate reported in patients with BD compared to controls (RR=1.67, 95% CI 1.32-2.12, p<0.001). We also observed that more than half of the BD participants had abdominal obesity (i.e., prevalence of 51.1%; 95% CI, 45.0-57.3%).

LIMITATIONS

A significant degree of heterogeneity was detected. Sources of heterogeneity included differences in study designs, inclusion criteria, measurement tools, and data analysis methods.

CONCLUSION

Bipolar disorder is associated with a higher prevalence of T2DM, IFG, general obesity, and abdominal obesity. Type 2 diabetes mellitus and obesity are significantly more prevalent in patients with BD than in their age- and gender-matched controls.

STUDY REGISTRATION

CRD42021258431.

Weight gain and comorbidities associated with oral second-generation antipsychotics: analysis of real-world data for patients with schizophrenia or bipolar I disorder

BACKGROUND

Many second-generation antipsychotics (SGAs) are associated with weight gain and cardiometabolic effects. Antipsychotic-associated weight gain is linked to treatment interruptions, potentially increasing risk of relapse and hospitalization. This retrospective study assessed clinically significant weight gain (CSWG), treatment interruptions, and development of cardiometabolic conditions in patients with schizophrenia (SZ) or bipolar I disorder (BD-I) following initiation of oral SGAs with moderate to high weight gain risk.

METHODS

Patients with no prior use of moderate to high weight gain risk oral SGAs were identified from patient-level medical/pharmacy claims and electronic medical records (January 2013-February 2020; OM1 Real-World Data Cloud). Those with ≥ 1 weight measurement in both the 12 months preceding and 3 months after SGA initiation (index date) were analyzed for continuous changes in weight, CSWG (≥ 7% and ≥ 10% increases from baseline), treatment interruptions (switches/discontinuations), and development of cardiometabolic conditions.

RESULTS

Median follow-up times in the SZ (n = 8174) and BD-I (n = 9142) cohorts were 153.4 and 159.4 weeks, respectively; 45.5% and 50.7% were obese at baseline. Mean (SD) percent weight increase during treatment was 3.3% (7.2) and 3.7% (7.0) for patients with SZ and BD-I, respectively, and was highest for underweight/normal weight patients (SZ: 4.8% [8.1]; BD-I: 5.5% [8.7]). More than 96% had treatment interruptions during follow-up, primarily discontinuations. CSWG and treatment interruptions occurred within a median of 13 and 14 weeks after treatment initiation, respectively. Of patients with CSWG and treatment interruptions, approximately 75% did not return to baseline weight during follow-up. Among those without baseline cardiometabolic conditions, 14.7% and 11.3% of patients with SZ or BD-I, respectively, developed ≥ 1 condition over 12 months post-index. Incidence was generally highest among those who were overweight/obese at baseline and those who experienced CSWG.

CONCLUSIONS

In this analysis of real-world data, both weight gain and treatment interruptions occurred early in treatment for patients with SZ or BD-I. Treatment-associated weight gain persisted despite switching or discontinuing index treatment. Additionally, cardiometabolic morbidity increased within 12 months of treatment initiation. Patients with SZ or BD-I are at greater risk than the general population for cardiometabolic conditions; weight gain associated with SGAs may exacerbate these health risks.

Prevalence and associated factors of obesity and overweight in Chinese patients with bipolar disorder

OBJECT

Despite abundant literature demonstrating a high prevalence of obesity and overweight in people with bipolar disorder (BD), little is known about this topic in China. Therefore, we assessed the prevalence and associated factors of obesity and overweight among inpatients with BD in our hospital, one of the largest public psychiatric hospitals in China.

METHODS

In this retrospective, cross-sectional study, 1,169 inpatients ≥18 years with BD during 2019 were included. Obesity was defined as having a BMI ≥25 kg/m², and overweight was defined as having a BMI from 23 kg/m² to <25 kg/m². Binary logistic regression analysis was performed to identify factors associated with obesity and overweight.

RESULTS

The prevalence of obesity and overweight was 21.0% and 32.2% in patients with BD, respectively. Compared to patients with overweight and normal weight, patients with obesity were older, had a longer duration of BD and a longer length of hospital stay, had a higher prevalence of diabetes and hypertension, and had a higher level of all metabolic indices, except for HDL cholesterol. Binary logistic regression analysis showed that duration of BD, uric acid, alanine aminotransferase (ALT), triglyceride, and LDL cholesterol were significantly associated with obesity, and male sex and uric acid level were significantly associated with overweight (p < 0.05).

CONCLUSIONS

Obesity and overweight were fairly prevalent in Chinese BD patients, and several factors were related to obesity and overweight. The results of the present study call for the need to implement early screening, prevention and interventions for obesity and overweight in patients with BD in China.

Non-mental diseases associated with ADHD across the lifespan: Fidgety Philipp and Pippi Longstocking at risk of multimorbidity?

Several non-mental diseases seem to be associated with an increased risk of ADHD and ADHD seems to be associated with increased risk for non-mental diseases. The underlying trajectories leading to such brain-body co-occurrences are often unclear - are there direct causal relationships from one disorder to the other, or does the sharing of genetic and/or environmental risk factors lead to their occurring together more frequently or both? Our goal with this narrative review was to provide a conceptual synthesis of the associations between ADHD and non-mental disease across the lifespan. We discuss potential shared pathologic mechanisms, genetic background and treatments in co-occurring diseases. For those co-occurrences for which published studies with sufficient sample sizes exist, meta-analyses have been published by others and we discuss those in detail. We conclude that non-mental diseases are common in ADHD and vice versa and add to the disease burden of the patient across the lifespan. Insufficient attention to such co-occurring conditions may result in missed diagnoses and suboptimal treatment in the affected individuals.

Multimorbidity and Its Outcomes Among Patients Attending Psychiatric Care Settings: An Observational Study From Odisha, India

Background: Multimorbidity, the presence of two or more chronic health conditions is linked to premature mortality among psychiatric patients since the presence of one can further complicate the management of either. Little research has focused on the magnitude and effect of multimorbidity among psychiatric patients in low-and middle-income settings. Our study, provides the first ever data on multimorbidity and its outcomes among patients attending psychiatric clinics in Odisha, India. It further explored whether multimorbidity was associated with higher medical expenditure and the interaction effect of psychiatric illness on this association.

Methods: This cross-sectional study included 500 adult patients presenting to the psychiatric clinic of a medical college hospital in Odisha over a period of 6 months (February 2019–July 2019). A validated structured questionnaire, “multimorbidity assessment questionnaire for psychiatric care” (MAQ-PsyC) was used for data collection. We used multinomial logistic model for the effect estimation. Odds ratios (OR) and 95% confidence intervals (CI) for high healthcare utilization and expenditure were calculated by number and pattern of multimorbidity. Data was analyzed by STATA 14.

Results: Half (50%) of the psychiatric outpatients had multimorbidity. The relative probabilities of having one additional condition were 5.3 times (RRR = 5.3; 95% CI: 2.3, 11.9) and multiple morbidities were 6.6 times (RRR = 6.6; 95%CI: 3.3, 13.1) higher for patients in 60+ age group. Healthcare utilization i.e., medication use and physician consultation was significantly higher for psychiatric conditions such as mood disorders, schizophrenia, schizotypal and delusional disorders, and for hypertension, cancer, diabetes, among somatic conditions. Out of pocket expenditure (OOPE) was found to be highest for laboratory investigations, followed by medicines and transport expenditure. Within psychiatric conditions, mood disorders incurred highest OOPE ($93.43) while hypertension was the most leading for OOPE in physical morbidities ($93.43). Psychiatric illnesses had a significant interaction effect on the association between multimorbidity and high medical expenditure (P = 0.001).

Conclusion: Multimorbidity is highly prevalent in psychiatric patients associated with significantly high healthcare utilization and medical expenditure. Such disproportionate effect of psychiatric multimorbidity on healthcare cost and use insinuates the need for stronger financial protection and tailor-made clinical decision making for these vulnerable patient subgroups.